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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16

Experimental investigation of a DISI production engine fuelled with methanol, ethanol, butanol, and iso-stoichiometric alcohol blends

Stricter CO2 and emissions regulations are pushing spark ignition engines more and more towards downsizing, enabled through direct injection and turbocharging. The advantages which come with direct injection, such as increased charge density and an elevated knock resistance, are even more pronounced when using low carbon number alcohols instead of gasoline. This is mainly due to the higher heat of vaporization and the lower air-to-fuel ratio of light alcohols such as methanol, ethanol and butanol. These alcohols are also attractive alternatives to gasoline because they can be produced from renewable resources. Because they are liquid, they can be easily stored in a vehicle. In this respect, the performance and engine-out emissions (NOx, CO, HC and PM) of methanol, ethanol and butanol were examined on a 4 cylinder 2.4 DI production engine and are compared with those on neat gasoline. Additionally, measurements were done for E85 and a methanol-gasoline blend with the same air-to-fuel ratio as E85 because this ‘iso-stoichiometric’ methanol-gasoline blend shows very few differences in physical properties to E85 and has the potential to be used as ‘drop-in’ fuel for flex-fuel vehicles. It is shown that the brake thermal efficiency when running on alcohol fuels is significantly better than with gasoline while emitting fewer emissions. In a knock limited case for gasoline, the brake thermal efficiency on methanol was more than 5 percentage points better than on gasoline. The engine test results also confirm that, from an engine control point of view, the ‘iso-stoichiometric’ methanol-gasoline blend can indeed be used as a ‘drop-in’ fuel for E85.

Sileghem, Louis↗

Achieving Diesel-Like Efficiency in a High Stroke-to-Bore Ratio DISI Engine under Stoichiometric Operation

This work explores pathways to achieve diesel-like, high-efficiency combustion with stoichiometric 3-way catalyst compatible spark ignition (SI). A high stroke-to-bore engine design (1.5:1) with cooled exhaust gas recirculation (EGR) and high compression ratio (r c ) was used to improve engine efficiency by up to 30% compared with a production turbocharged gasoline direct injection spark ignition engine. To achieve efficiency improvements, engine experiments were coupled with computational fluid dynamics simulations to guide and explain experimental trends between the original engine and the high stroke-to-bore ratio design (1.5:1). The effects of EGR and late intake valve closing (IVC) and fuel characteristics are investigated through their effects on knock mitigation. Direct injection of 91 RON E10 gasoline, 99 RON E0 gasoline, and liquified petroleum gas (i.e., propane/autogas) were evaluated with geometric rc ranging from 13.3:1 to 16.8:1. Finally, engine experiments demonstrated 47% gross thermal efficiency, and 45% net thermal efficiency at stoichiometric engine operation, at up to 17 bar IMEP and 2000 r/min with 16.8:1 rc.

42 ENGINEERING↗

Effects of Turbulence and Temperature Fluctuations on Knock Development in an Ethanol/Air Mixture

The effects of turbulence on knock development and intensity for a thermally inhomogeneous stoichiometric ethanol/air mixture at a representative end-gas autoignition condition in internal combustion engines are investigated using direct numerical simulations with a skeletal reaction mechanism. Two- and three-dimensional simulations are performed by varying the most energetic length scale of temperature, \(l_T\) , and its relative ratio with the most energetic length scale of turbulence, \(l_T/l_e\) , together with two different levels of the turbulent velocity fluctuation, \(u'\) . It is found that \(l_T\) / \(l_e\) and the ratio of ignition delay time to eddy-turnover time, \(\tau _{ig}/\tau _t\) , are the key parameters that control the detonation development. An increase in either \(l_T\) or \(l_e\) enhances the detonation propensity by allowing a longer run-up distance for the detonation development. The characteristic length scale of the temperature field, \(l_T\) , is significantly modified by high turbulence intensity achieved by a large \(l_e\) and \(u'\) . The intense turbulence mixing effectively distributes the initial temperature field to broader scales to support the developing detonation waves, thereby increasing the likelihood of the detonation formation. On the contrary, high turbulence intensity with a short mixing time scale, achieved by a small \(l_e\) and a large \(u'\) , reduces the super-knock intensity attributed to the finer broken-up structures of detonation waves. Either \(\tau _{ig}/\tau _t\) less than unity or \(l_e = l_T\) even with a large \(u'\) is found to have no significant effect on super-knock mitigation. Finally, high turbulent intensity may induce high-pressure spikes comparable to the von Neumann spike. Overall, increased temperature and pressure by combustion heating, noticeably after the peak of heat release rate, significantly enhance the collision and interaction of multiple emerging autoignition fronts near the ending combustion process, resulting in localized high-pressure spikes.

42 ENGINEERING↗

The Impact of LPG Composition on Performance, Emissions, and Combustion Characteristics of a Pre-mixed Spark-Ignited CFR Engine

Research on alternative fuels has made significant progress as demands for cleaner and more efficient engine operation intensifies. Liquefied petroleum gas (LPG) can offer a potential alternative fuel route in the Diesel fuel dominated heavy-duty transportation sector due to its low cost, high anti-knock limit relative to gasoline, and reduced emission levels. In this work, experimental investigations are performed to study the effects of LPG compositions on performance, emissions, and combustion behavior of a spark-ignited (SI) cooperative fuel research (CFR) engine under stoichiometric conditions. Four LPG blends (chemically pure propane, a representative US blend, HD-5, and a representative European blend) representing the present LPG market are chosen. The impact of fuel composition is studied under different compression ratios (CR), ranging from 7:1 to 10:1 with one-unit increments, and at constant engine speed, intake manifold air pressure (IMAP) and 50% burn crank angle (CA50). The results show that fuel composition has minimal effect on engine efficiency over the CR range 7:1 to 10:1. Engine-out emissions are substantially affected by fuel compositions with the representative European blend indicating higher unburned hydrocarbon (UHC) emissions, particularly at higher CR. The representative US blend emits the lowest brake specific CO (bsCO) averaged over the tested CR range. With the increase of CR, end-gas autoignition intensifies for all blends and the representative European blend demonstrates the highest knock intensity of all tested blends, due to the presence of the more reactive fuel component, n-butane.

Fosudo, Toluwalase↗

Determination of a most representative cycle from cylinder pressure ensembles via statistical method using distribution skewness

In internal combustion engine research, cylinder pressure measurements provide valuable information about the underlying thermodynamic and combustion processes, and are typically collected in ensembles of several 100 traces. Although in some particular fields of combustion research all traces are analyzed, in most cases only one trace is studied because analyzing all the traces is impractical due to the large number of collected samples. Instead, an ensemble-averaged pressure trace is commonly calculated and used for analysis. However, this pressure trace is highly smoothed and dynamic information is lost during the averaging process. With the average trace, pressure rise rates are lower and pressure oscillations such as the ones resulting from combustion knock are lost. In this work, a statistical method was developed to determine the “most representative cycle,” which is the cycle from the ensemble that has the pressure trace most representative of the engine operating condition. Eleven characteristic parameters are computed from each pressure trace and probabilistic distributions are obtained for each of the parameters using all the traces in the ensemble. Finally, the most representative cycle is selected by means of a cost function minimization. The benefits of this method are illustrated using experimental data from four very different engine platforms, under four different combustion modes and over a range of operating conditions.

42 ENGINEERING↗

The Insertion Green Monster (iGM) Method for Expression of Multiple Exogenous Genes in Yeast

Being a simple eukaryotic organism, Saccharomyces cerevisiae provides numerous advantages for expression and functional characterization of proteins from higher eukaryotes, including humans. However, studies of complex exogenous pathways using yeast as a host have been hampered by the lack of tools to engineer strains expressing a large number of genetic components. In addition to inserting multiple genes, it is often desirable to knock out or replace multiple endogenous genes that might interfere with the processes studied. Here, we describe the “insertion Green Monster” (iGM) set of expression vectors that enable precise insertion of many heterologous genes into the yeast genome in a rapid and reproducible manner and permit simultaneous replacement of selected yeast genes. As a proof of principle, we have used the iGM method to replace components of the yeast pathway for methionine sulfoxide reduction with genes encoding the human selenoprotein biosynthesis machinery and generated a single yeast strain carrying 11 exogenous components of the selenoprotein biosynthetic pathway in precisely engineered loci.

Saccharomyces cerevisiae↗

SU-E-T-523: On the Radiobiological Impact of Lateral Scatter in Proton Beams

Introduction: In proton therapy, justified concern has been voiced with respect to an increased efficiency in cell kill at the distal end of the Bragg peak. This coupled with range uncertainty is a counter indication to use the Bragg peak to define the border of a treated volume with a critical organ. An alternative is to use the lateral edge of the proton beam, obtaining more robust plans. We investigate the spectral and biological effects of the lateral scatter . Methods: A general purpose Monte Carlo simulation engine (MCNPX 2.7c) installed on a Scientific Linux cluster, calculated the dose deposition spectrum of protons, knock on electrons and generated neutrons for a proton beam with maximal kinetic energy of 200MeV. Around the beam at different positions in the beam direction the spectrum is calculated in concentric rings of thickness 1cm. The deposited dose is converted to a double strand break map using an analytical expression.based on micro dosimetric calculations using a phenomenological Monte Carlo code (MCDS). A strict version of RBE is defined as the ratio of generation of double strand breaks in the different modalities. To generate the reference a Varian linac was modelled in MCNPX and the generated electron dose deposition spectrum was used . Results: On a pristine point source 200MeV beam the RBE before the Bragg peak was of the order of 1.1, increasing to 1.7 right behind the Bragg peak. When using a physically more realistic beam of 10cm diameter the effect was smaller. Both the lateral dose and RBE increased with increasing beam depth, generating a dose deposition with mixed biological effect. Conclusions: The dose deposition in proton beams need to be carefully examined because the biological effect will be different depending on the treatment geometry. Deeply penetrating proton beams generate more biologically effective lateral scatter.

07 ISOTOPE AND RADIATION SOURCES↗

Hydrocarbon Speciation in Blended Gasoline-Natural Gas Operation on a Spark-Ignition Engine

The high octane rating and more plentiful domestic supply of natural gas make it an excellent alternative to gasoline. Recent studies have shown that using natural gas in dual fuel engines provides one possible strategy for leveraging the advantages of both natural gas and gasoline. In particular, such engines been able to improve overall engine efficiencies and load capacity when they leverage direct injection of the natural gas fuel. While the benefits of these engine concepts are still being explored, differences in fuel composition, combustion process and in-cylinder mixing could lead to dramatically different emissions which can substantially impact the effectiveness of the engine’s exhaust aftertreatment system. In order to explore this topic, this study examined the variations in speciated hydrocarbon emissions which occur for different fuel blends of E10 and compressed natural gas and for different fuel injection strategies on a spark-ignition engine. Results indicate that hydrocarbon emissions are clearly impacted by the base fuel structure and that differences in the underlying fuel chemistry can produce significant variations (over 300%) in the emissions of various hydrocarbon species. Injection strategy plays a role in the amount of mixing achieved and as such impacts emissions, but fuel structure is a much more significant factor. By using 50-75% percent compressed natural gas (CNG) at the lower load points, total methane and non-methane emissions could be reduced by up to 37% without any significant drop in engine efficiency. At the higher load points, usage of 100% CNG is more advantageous due to the knock constraints.

Hall, Carrie↗

Numerical Investigation of a Central Fuel Property Hypothesis Under Boosted Spark-Ignition Conditions

In the present work, a central fuel property hypothesis (CFPH), which states that fuel properties are sufficient to provide an indication of a fuel’s performance irrespective of its chemical composition, was numerically investigated. In particular, the objective of the study was to determine whether Research Octane Number (RON) and Motor Octane Number (MON), as fuel properties, are sufficient to describe a fuel’s knock-limited performance under boosted spark-ignition (SI) conditions within the framework of CFPH. To this end, four TPRF-bioblendstock surrogates having different compositions but matched RON (=98) and MON (=90), were first generated using a non-linear regression model based on artificial neural network (ANN). Additionally, three unconventional bioblendstocks were included in the analysis: di-isobutylene (DIB), isobutanol, and Anisole. Skeletal reaction mechanisms were generated for the TPRF-DIB, TPRF-isobutanol, and TPRF-anisole blends from a detailed kinetic mechanism. Thereafter, numerical simulations were performed for the fuel surrogates using the skeletal mechanisms and a virtual cooperative fuel research (CFR) engine model, under a representative boosted operating condition. In the computational fluid dynamics (CFD) model, the G-equation approach was employed to track the turbulent flame front and the well-stirred reactor model combined with the multi-zone binning strategy was used to capture auto-ignition in the end-gas. In addition, laminar flame speed (LFS) was tabulated for each blend as a function of pressure, temperature, and equivalence ratio a priori, and the lookup tables were used to prescribe laminar flame speed as an input to the G-equation model. Parametric spark timing sweeps were performed for each fuel blend to determine the corresponding knock-limited spark advance (KLSA) and 50% burn point (CA50) at the respective KLSA timing. It was observed that despite same RON, MON, and engine operating conditions, the TPRF-anisole blend exhibited markedly different knock-limited performance from the other three blends. This deviation from the octane index (OI) expectation was shown to be caused by differences in laminar flame speed. However, it was found that relatively large fuel-specific differences in LFS (>20%) would have to be present to cause any appreciable deviation from the OI framework. Otherwise, RON and MON would still be robust enough to predict a fuel’s knock-limited performance.

42 ENGINEERING↗

13 C Metabolic Flux Analysis for Systematic Metabolic Engineering of S. cerevisiae for Overproduction of Fatty Acids

Efficient redirection of microbial metabolism into the abundant production of desired bioproducts remains non-trivial. Here, we used flux-based modeling approaches to improve yields of fatty acids in Saccharomyces cerevisiae. We combined 13 C labeling data with comprehensive genome-scale models to shed light onto microbial metabolism and improve metabolic engineering efforts. We concentrated on studying the balance of acetyl-CoA, a precursor metabolite for the biosynthesis of fatty acids. A genome-wide acetyl-CoA balance study showed ATP citrate lyase from Yarrowia lipolytica as a robust source of cytoplasmic acetyl-CoA and malate synthase as a desirable target for downregulation in terms of acetyl-CoA consumption. These genetic modifications were applied to S. cerevisiae WRY2, a strain that is capable of producing 460 mg/L of free fatty acids. With the addition of ATP citrate lyase and downregulation of malate synthase, the engineered strain produced 26% more free fatty acids. Further increases in free fatty acid production of 33% were obtained by knocking out the cytoplasmic glycerol-3-phosphate dehydrogenase, which flux analysis had shown was competing for carbon flux upstream with the carbon flux through the acetyl-CoA production pathway in the cytoplasm. In total, the genetic interventions applied in this work increased fatty acid production by ~70%.

-omics data↗

What fuel properties enable higher thermal efficiency in spark-ignited engines?

The Co-Optimization of Fuels and Engines (Co-Optima) initiative from the US Department of Energy aims to co-develop fuels and engines in an effort to maximize energy efficiency and the utilization of renewable fuels. Many of these renewable fuel options have fuel chemistries that are different from those of petroleum-derived fuels. Because practical market fuels need to meet specific fuel-property requirements, a chemistry-agnostic approach to assessing the potential benefits of candidate fuels was developed using the Central Fuel Property Hypothesis (CFPH). The CFPH states that fuel properties are predictive of the performance of the fuel, regardless of the fuel's chemical composition. In order to use this hypothesis to assess the potential of fuel candidates to increase efficiency in spark-ignition (SI) engines, the individual contributions towards efficiency potential in an optimized engine must be quantified in a way that allows the individual fuel properties to be traded off for one another. This review article begins by providing an overview of the historical linkages between fuel properties and engine efficiency, including the two dominant pathways currently being used by vehicle manufacturers to reduce fuel consumption. Then, a thermodynamic-based assessment to quantify how six individual fuel properties can affect efficiency in SI engines is performed: research octane number, octane sensitivity, latent heat of vaporization, laminar flame speed, particulate matter index, and catalyst light-off temperature. The relative effects of each of these fuel properties is combined into a unified merit function that is capable of assessing the fuel property-based efficiency potential of fuels with conventional and unconventional compositions.

42 ENGINEERING↗

Effects of Gasoline Composition and Operating Parameters on the Response of End-Gas Autoignition to Nitric Oxide in a Lean-Burn DI-SI Engine

Lean operation of spark-ignition engines can lead to engine thermal efficiency gains and lower NOx emissions due to reduced combustion temperatures. Yet, lean operation could still face challenges in end-gas autoignition and knock generation due to higher intake pressures and trapped NO in the residual gas. Here, this study evaluates the impact of NO on end-gas autoignition for two gasoline fuels with similar octane rating but different composition: high cycloalkane fuel (HCA) and high olefin fuel (HO). Experiments were performed at stoichiometric and lean (λ = 2) conditions and at two engine speeds of 1400 rpm and 2000 rpm. Accompanying chemical kinetics simulations in CHEMKIN revealed that the mechanisms controlling the effect of NO on autoignition are similar λ = 2 and λ = 1, with NO + HO 2 = NO 2 + OH being the main pathway for enhancing reactivity by promoting low-temperature heat release (LTHR). The compositionally different fuels reacted differently to NO seeding and engine speed, and differences were augmented at λ = 2 compared to λ = 1 as the end-gas autoignition shifted to the low temperature regime. HO, which has inherent low temperature chemistry, was strongly impacted by engine speed at low NO seeding levels, with no noticeable peak of LTHR detected at 2000 rpm. On the other hand, LTHR of HCA was marginally affected by shortened residence time at higher engine speed as NO + HO 2 reaction was not greatly affected by shorter time scales, since HO 2 production was sustained even at 2000 rpm to support OH generation from NO + HO 2 . Contrary to HO, HCA exhibited greater sensitivity to NO seeding, as the increased OH production at higher NO concentrations offset the OH-quenching effect of cyclopentane, which accounts for 28.6% of HCA’s composition. Consequently, a sensitivity analysis revealed that fuels with weak inherent low-temperature chemistry, like HCA, are likely to be more sensitive to variations in NO concentration and charge temperature, whereas fuels with strong low temperature chemistry are more sensitive to variations in end-gas λ and intake pressure.

Energy↗

Octane Requirements of Lean Mixed-Mode Combustion in a Direct-Injection Spark-Ignition Engine

Here, this study investigates the octane requirements of a hybrid flame propagation and controlled autoignition mode referred to as mixed-mode combustion (MMC), which allows for strong control over combustion parameters via a spark-initiated deflagration phase. Due to the throughput limitations associated with both experiments and 3-D computational fluid dynamics calculations, a hybrid 0-D and 1-D modeling methodology was developed, supported by experimental validation data. This modeling approach relied on 1-D, two-zone engine simulations to predict bulk in-cylinder thermodynamic conditions over a range of engine speeds, compression ratios, intake pressures, trapped residual levels, fueling rates, and spark timings. Those predictions were then transferred to a 0-D chemical kinetic model, which was used to evaluate the autoignition behavior of fuels when subjected to temperature–pressure trajectories of interest. Finally, the predicted autoignition phasings were screened relative to the progress of the modeled deflagration-based combustion in order to determine if an operating condition was feasible or infeasible due to knock or stability limits. The combined modeling and experimental results reveal that MMC has an octane requirement similar to modern stoichiometric spark-ignition engines in that fuels with high research octane number (RON) and high octane sensitivity (S) enable higher loads. Experimental trends with varying RON and S were well predicted by the model for 1000 and 1400 rpm, confirming its utility in identifying the compatibility of a fuel’s autoignition behavior with an engine configuration and operating strategy. However, the model was not effective in predicting (nor designed to predict) operability limits due to cycle-to-cycle variations, which experimentally inhibited operation of some fuels at 2000 rpm. Putting the operable limits and efficiency from MMC in the context of a state-of-the-art engine, the MMC showed superior efficiencies over the range investigated, demonstrating the potential to further improve fuel economy.

33 ADVANCED PROPULSION SYSTEMS↗